90 lines
3.2 KiB
Python
90 lines
3.2 KiB
Python
from pathlib import Path
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import folder_paths
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import comfy.utils
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import comfy.sd
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from .logger import logger
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from .utils_model import get_available_motion_loras, get_motion_lora_path
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from .motion_lora import MotionLoraInfo, MotionLoraList
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class AnimateDiffLoraLoader:
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"lora_name": (get_available_motion_loras(),),
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"strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 10.0, "step": 0.001}),
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},
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"optional": {
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"prev_motion_lora": ("MOTION_LORA",),
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}
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}
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RETURN_TYPES = ("MOTION_LORA",)
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CATEGORY = "Animate Diff 🎭🅐🅓"
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FUNCTION = "load_motion_lora"
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def load_motion_lora(self, lora_name: str, strength: float, prev_motion_lora: MotionLoraList=None):
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if prev_motion_lora is None:
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prev_motion_lora = MotionLoraList()
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else:
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prev_motion_lora = prev_motion_lora.clone()
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# check if motion lora with name exists
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lora_path = get_motion_lora_path(lora_name)
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if not Path(lora_path).is_file():
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raise FileNotFoundError(f"Motion lora with name '{lora_name}' not found.")
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# create motion lora info to be loaded in AnimateDiff Loader
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lora_info = MotionLoraInfo(name=lora_name, strength=strength)
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prev_motion_lora.add_lora(lora_info)
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return (prev_motion_lora,)
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class MaskedLoraLoader:
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def __init__(self):
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self.loaded_lora = None
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "model": ("MODEL",),
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"clip": ("CLIP", ),
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"lora_name": (folder_paths.get_filename_list("loras"), ),
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"strength_model": ("FLOAT", {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01}),
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"strength_clip": ("FLOAT", {"default": 1.0, "min": -20.0, "max": 20.0, "step": 0.01}),
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}}
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#RETURN_TYPES = ()
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RETURN_TYPES = ("MODEL", "CLIP")
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FUNCTION = "load_lora"
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CATEGORY = "loaders"
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def load_lora(self, model, clip, lora_name, strength_model, strength_clip):
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if strength_model == 0 and strength_clip == 0:
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return (model, clip)
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lora_path = folder_paths.get_full_path("loras", lora_name)
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lora = None
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if self.loaded_lora is not None:
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if self.loaded_lora[0] == lora_path:
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lora = self.loaded_lora[1]
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else:
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temp = self.loaded_lora
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self.loaded_lora = None
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del temp
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if lora is None:
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lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
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self.loaded_lora = (lora_path, lora)
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from pathlib import Path
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with open(Path(__file__).parent.parent.parent / "sd_lora_keys.txt", "w") as lfile:
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for key in lora:
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lfile.write(f"{key}:\t{lora[key].size()}\n")
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#model_lora, clip_lora = comfy.sd.load_lora_for_models(model, clip, lora, strength_model, strength_clip)
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#return (model_lora, clip_lora)
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return (model, clip)
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